11 citations · 45 across the 18 of their papers we have counts for
4 papers · 1 filter
EXPLAIN, EDIT, GENERATE: Rationale-Sensitive Counterfactual Data Augmentation for Multi-hop Fact Verification
Yingjie Zhu, Jiasheng Si, Yibo Zhao +3
Automatic multi-hop fact verification task has gained significant attention in recent years. Despite impressive results, these well-designed models perform poorly on out-of-domain…
Explainable Topic-Enhanced Argument Mining from Heterogeneous Sources
Jiasheng Si, Yingjie Zhu, Xingyu Shi +2
Given a controversial target such as ``nuclear energy'', argument mining aims to identify the argumentative text from heterogeneous sources. Current approaches focus on exploring b…
Feature Representation Learning for NL2SQL Generation Based on Coupling and Decoupling
Chenduo Hao, Xu Zhang, Chuanbao Gao +1
The NL2SQL task involves parsing natural language statements into SQL queries. While most state-of-the-art methods treat NL2SQL as a slot-filling task and use feature representatio…
Consistent Multi-Granular Rationale Extraction for Explainable Multi-hop Fact Verification
Jiasheng Si, Yingjie Zhu, Deyu Zhou
The success of deep learning models on multi-hop fact verification has prompted researchers to understand the behavior behind their veracity. One possible way is erasure search: ob…